Overview

Brought to you by YData

Dataset statistics

Number of variables14
Number of observations9357
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.1 MiB
Average record size in memory120.0 B

Variable types

DateTime2
Numeric12

Alerts

AH is highly overall correlated with PT08.S4(NO2) and 1 other fieldsHigh correlation
C6H6(GT) is highly overall correlated with CO(GT) and 7 other fieldsHigh correlation
CO(GT) is highly overall correlated with C6H6(GT) and 7 other fieldsHigh correlation
NO2(GT) is highly overall correlated with C6H6(GT) and 6 other fieldsHigh correlation
NOx(GT) is highly overall correlated with C6H6(GT) and 6 other fieldsHigh correlation
PT08.S1(CO) is highly overall correlated with C6H6(GT) and 7 other fieldsHigh correlation
PT08.S2(NMHC) is highly overall correlated with C6H6(GT) and 7 other fieldsHigh correlation
PT08.S3(NOx) is highly overall correlated with C6H6(GT) and 7 other fieldsHigh correlation
PT08.S4(NO2) is highly overall correlated with AH and 7 other fieldsHigh correlation
PT08.S5(O3) is highly overall correlated with C6H6(GT) and 7 other fieldsHigh correlation
RH is highly overall correlated with THigh correlation
T is highly overall correlated with AH and 2 other fieldsHigh correlation

Reproduction

Analysis started2025-04-07 00:07:46.805207
Analysis finished2025-04-07 00:08:05.835332
Duration19.03 seconds
Software versionydata-profiling vv4.16.1
Download configurationconfig.json

Variables

Date
Date

Distinct391
Distinct (%)4.2%
Missing0
Missing (%)0.0%
Memory size146.2 KiB
Minimum2004-03-10 00:00:00
Maximum2005-04-04 00:00:00
Invalid dates0
Invalid dates (%)0.0%
2025-04-07T00:08:05.937691image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-07T00:08:06.092144image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

Time
Date

Distinct24
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size146.2 KiB
Minimum2025-04-07 00:00:00
Maximum2025-04-07 23:00:00
Invalid dates0
Invalid dates (%)0.0%
2025-04-07T00:08:06.208318image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-07T00:08:06.310812image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=24)

CO(GT)
Real number (ℝ)

High correlation 

Distinct97
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.1527495
Minimum0.1
Maximum11.9
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size146.2 KiB
2025-04-07T00:08:06.431290image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum0.1
5-th percentile0.5
Q11.2
median2.1527495
Q32.6
95-th percentile4.7
Maximum11.9
Range11.8
Interquartile range (IQR)1.4

Descriptive statistics

Standard deviation1.3160683
Coefficient of variation (CV)0.61134298
Kurtosis3.9104494
Mean2.1527495
Median Absolute Deviation (MAD)0.75274954
Skewness1.5124615
Sum20143.277
Variance1.7320358
MonotonicityNot monotonic
2025-04-07T00:08:06.914900image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2.152749544 1683
 
18.0%
1 305
 
3.3%
1.4 279
 
3.0%
1.6 275
 
2.9%
1.5 273
 
2.9%
1.1 262
 
2.8%
0.7 260
 
2.8%
1.7 258
 
2.8%
1.3 253
 
2.7%
0.8 251
 
2.7%
Other values (87) 5258
56.2%
ValueCountFrequency (%)
0.1 33
 
0.4%
0.2 45
 
0.5%
0.3 98
 
1.0%
0.4 160
1.7%
0.5 217
2.3%
0.6 244
2.6%
0.7 260
2.8%
0.8 251
2.7%
0.9 248
2.7%
1 305
3.3%
ValueCountFrequency (%)
11.9 1
< 0.1%
11.5 1
< 0.1%
10.2 2
< 0.1%
10.1 1
< 0.1%
9.9 1
< 0.1%
9.5 1
< 0.1%
9.4 1
< 0.1%
9.3 1
< 0.1%
9.2 1
< 0.1%
9.1 2
< 0.1%

PT08.S1(CO)
Real number (ℝ)

High correlation 

Distinct3541
Distinct (%)37.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1102.9329
Minimum647.25
Maximum2039.75
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size146.2 KiB
2025-04-07T00:08:07.040207image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum647.25
5-th percentile811.45
Q1937.5
median1066.75
Q31238.75
95-th percentile1509.4
Maximum2039.75
Range1392.5
Interquartile range (IQR)301.25

Descriptive statistics

Standard deviation218.20156
Coefficient of variation (CV)0.19783756
Kurtosis0.20842305
Mean1102.9329
Median Absolute Deviation (MAD)145.25
Skewness0.71145677
Sum10320143
Variance47611.921
MonotonicityNot monotonic
2025-04-07T00:08:07.173145image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
954.25 12
 
0.1%
986.75 12
 
0.1%
1099.5 12
 
0.1%
969 11
 
0.1%
988.25 11
 
0.1%
890.75 11
 
0.1%
1009.25 11
 
0.1%
925.75 11
 
0.1%
888 11
 
0.1%
1054 10
 
0.1%
Other values (3531) 9245
98.8%
ValueCountFrequency (%)
647.25 1
< 0.1%
648.75 1
< 0.1%
654.75 1
< 0.1%
666.75 1
< 0.1%
667 1
< 0.1%
667.25 1
< 0.1%
669.25 1
< 0.1%
676.25 1
< 0.1%
677.5 1
< 0.1%
678.5 1
< 0.1%
ValueCountFrequency (%)
2039.75 1
< 0.1%
2007.75 1
< 0.1%
1982.25 1
< 0.1%
1974.75 1
< 0.1%
1972.5 1
< 0.1%
1961.25 1
< 0.1%
1956 1
< 0.1%
1934 1
< 0.1%
1917.75 1
< 0.1%
1917 1
< 0.1%

C6H6(GT)
Real number (ℝ)

High correlation 

Distinct4138
Distinct (%)44.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean10.178838
Minimum0.14904774
Maximum63.741476
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size146.2 KiB
2025-04-07T00:08:07.313359image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum0.14904774
5-th percentile1.7439373
Q14.4771454
median8.2890854
Q314.096486
95-th percentile24.880728
Maximum63.741476
Range63.592429
Interquartile range (IQR)9.6193404

Descriptive statistics

Standard deviation7.5032954
Coefficient of variation (CV)0.73714656
Kurtosis2.3235595
Mean10.178838
Median Absolute Deviation (MAD)4.4532507
Skewness1.3371113
Sum95243.387
Variance56.299442
MonotonicityNot monotonic
2025-04-07T00:08:07.446620image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
6.849891944 13
 
0.1%
6.810174913 9
 
0.1%
10.18426339 9
 
0.1%
5.560495658 9
 
0.1%
4.04571731 9
 
0.1%
7.772386849 8
 
0.1%
6.291887126 8
 
0.1%
6.341278497 8
 
0.1%
5.544912139 8
 
0.1%
5.101134318 8
 
0.1%
Other values (4128) 9268
99.0%
ValueCountFrequency (%)
0.1490477388 2
< 0.1%
0.1649456884 1
< 0.1%
0.1719683734 1
< 0.1%
0.1815254092 2
< 0.1%
0.2127981659 1
< 0.1%
0.2241305792 1
< 0.1%
0.2406875551 1
< 0.1%
0.2420520143 1
< 0.1%
0.2671717608 1
< 0.1%
0.2700279111 1
< 0.1%
ValueCountFrequency (%)
63.74147645 1
< 0.1%
52.05406416 1
< 0.1%
50.77953259 1
< 0.1%
50.67281895 1
< 0.1%
50.63282602 1
< 0.1%
49.49209269 1
< 0.1%
49.4393052 1
< 0.1%
48.21877473 1
< 0.1%
47.67183594 1
< 0.1%
47.4771456 1
< 0.1%

PT08.S2(NMHC)
Real number (ℝ)

High correlation 

Distinct4134
Distinct (%)44.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean942.01956
Minimum383.25
Maximum2214
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size146.2 KiB
2025-04-07T00:08:07.573830image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum383.25
5-th percentile564.35
Q1736
median910.33333
Q31119
95-th percentile1425.55
Maximum2214
Range1830.75
Interquartile range (IQR)383

Descriptive statistics

Standard deviation267.86485
Coefficient of variation (CV)0.28435169
Kurtosis0.023542219
Mean942.01956
Median Absolute Deviation (MAD)189.08333
Skewness0.55717729
Sum8814477
Variance71751.58
MonotonicityNot monotonic
2025-04-07T00:08:07.718360image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
850.25 13
 
0.1%
713.25 9
 
0.1%
984.5 9
 
0.1%
791 9
 
0.1%
848.5 9
 
0.1%
825.25 8
 
0.1%
889.75 8
 
0.1%
768.5 8
 
0.1%
827.5 8
 
0.1%
790.25 8
 
0.1%
Other values (4124) 9268
99.0%
ValueCountFrequency (%)
383.25 2
< 0.1%
386.75 1
< 0.1%
388.25 1
< 0.1%
390.25 2
< 0.1%
396.5 1
< 0.1%
398.6666667 1
< 0.1%
401.75 1
< 0.1%
402 1
< 0.1%
406.5 1
< 0.1%
407 1
< 0.1%
ValueCountFrequency (%)
2214 1
< 0.1%
2006.75 1
< 0.1%
1983 1
< 0.1%
1981 1
< 0.1%
1980.25 1
< 0.1%
1958.75 1
< 0.1%
1957.75 1
< 0.1%
1934.5 1
< 0.1%
1924 1
< 0.1%
1920.25 1
< 0.1%

NOx(GT)
Real number (ℝ)

High correlation 

Distinct2467
Distinct (%)26.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean246.88125
Minimum2
Maximum1479
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size146.2 KiB
2025-04-07T00:08:07.849330image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum2
5-th percentile41
Q1112
median229
Q3284.2
95-th percentile652.96
Maximum1479
Range1477
Interquartile range (IQR)172.2

Descriptive statistics

Standard deviation193.41942
Coefficient of variation (CV)0.78345122
Kurtosis4.7616528
Mean246.88125
Median Absolute Deviation (MAD)100
Skewness1.8892018
Sum2310067.9
Variance37411.071
MonotonicityNot monotonic
2025-04-07T00:08:07.984884image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
246.8812516 1639
 
17.5%
65 37
 
0.4%
89 36
 
0.4%
41 36
 
0.4%
57 32
 
0.3%
46 31
 
0.3%
61 31
 
0.3%
51 31
 
0.3%
111 30
 
0.3%
72 30
 
0.3%
Other values (2457) 7424
79.3%
ValueCountFrequency (%)
2 1
 
< 0.1%
4 1
 
< 0.1%
6 1
 
< 0.1%
7 1
 
< 0.1%
8 1
 
< 0.1%
9 1
 
< 0.1%
10 3
< 0.1%
11 4
< 0.1%
12 4
< 0.1%
13 4
< 0.1%
ValueCountFrequency (%)
1479 1
< 0.1%
1389 2
< 0.1%
1369 1
< 0.1%
1358 1
< 0.1%
1345 1
< 0.1%
1310 1
< 0.1%
1301 1
< 0.1%
1290 1
< 0.1%
1253 1
< 0.1%
1247 1
< 0.1%

PT08.S3(NOx)
Real number (ℝ)

High correlation 

Distinct3868
Distinct (%)41.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean832.63493
Minimum322
Maximum2682.75
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size146.2 KiB
2025-04-07T00:08:08.122226image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum322
5-th percentile482.95
Q1654
median803.5
Q3967.5
95-th percentile1284.1
Maximum2682.75
Range2360.75
Interquartile range (IQR)313.5

Descriptive statistics

Standard deviation255.70881
Coefficient of variation (CV)0.30710795
Kurtosis2.6436104
Mean832.63493
Median Absolute Deviation (MAD)155.75
Skewness1.091018
Sum7790965
Variance65386.994
MonotonicityNot monotonic
2025-04-07T00:08:08.257842image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
829.5 11
 
0.1%
866.25 10
 
0.1%
683.25 10
 
0.1%
696.75 9
 
0.1%
767 9
 
0.1%
732.5 9
 
0.1%
793 9
 
0.1%
815.5 9
 
0.1%
911.5 9
 
0.1%
874.25 9
 
0.1%
Other values (3858) 9263
99.0%
ValueCountFrequency (%)
322 1
< 0.1%
324.5 1
< 0.1%
325.25 1
< 0.1%
328 1
< 0.1%
329.75 2
< 0.1%
333.5 1
< 0.1%
334.5 1
< 0.1%
339.5 1
< 0.1%
340 1
< 0.1%
340.75 1
< 0.1%
ValueCountFrequency (%)
2682.75 1
< 0.1%
2559.25 1
< 0.1%
2541.5 1
< 0.1%
2330.75 1
< 0.1%
2327 1
< 0.1%
2317.75 1
< 0.1%
2294 1
< 0.1%
2121.25 1
< 0.1%
2095.25 1
< 0.1%
2094.75 1
< 0.1%

NO2(GT)
Real number (ℝ)

High correlation 

Distinct1420
Distinct (%)15.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean113.07552
Minimum2
Maximum339.7
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size146.2 KiB
2025-04-07T00:08:08.390758image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum2
5-th percentile46
Q185.9
median113.07552
Q3133
95-th percentile194
Maximum339.7
Range337.7
Interquartile range (IQR)47.1

Descriptive statistics

Standard deviation43.911095
Coefficient of variation (CV)0.38833425
Kurtosis1.201328
Mean113.07552
Median Absolute Deviation (MAD)24.075515
Skewness0.68432463
Sum1058047.6
Variance1928.1843
MonotonicityNot monotonic
2025-04-07T00:08:08.520579image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
113.0755152 1642
 
17.5%
97 68
 
0.7%
95 66
 
0.7%
101 65
 
0.7%
114 63
 
0.7%
68 63
 
0.7%
99 62
 
0.7%
96 62
 
0.7%
107 61
 
0.7%
119 61
 
0.7%
Other values (1410) 7144
76.3%
ValueCountFrequency (%)
2 1
 
< 0.1%
3 1
 
< 0.1%
5 2
 
< 0.1%
7 1
 
< 0.1%
8 2
 
< 0.1%
9 2
 
< 0.1%
11 2
 
< 0.1%
12 2
 
< 0.1%
13 1
 
< 0.1%
14 5
0.1%
ValueCountFrequency (%)
339.7 1
< 0.1%
332.6 1
< 0.1%
325.9 1
< 0.1%
321.6 1
< 0.1%
312.4 1
< 0.1%
310.1 1
< 0.1%
309.2 1
< 0.1%
306.4 1
< 0.1%
301.1 1
< 0.1%
295.6 1
< 0.1%

PT08.S4(NO2)
Real number (ℝ)

High correlation 

Distinct4762
Distinct (%)50.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1453.1729
Minimum551
Maximum2775
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size146.2 KiB
2025-04-07T00:08:08.660247image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum551
5-th percentile882.9
Q11227
median1459.5
Q31668.25
95-th percentile2020.3
Maximum2775
Range2224
Interquartile range (IQR)441.25

Descriptive statistics

Standard deviation343.20136
Coefficient of variation (CV)0.2361738
Kurtosis0.10928572
Mean1453.1729
Median Absolute Deviation (MAD)218.25
Skewness0.20783151
Sum13597339
Variance117787.17
MonotonicityNot monotonic
2025-04-07T00:08:08.796083image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1490 10
 
0.1%
1363 9
 
0.1%
1623 8
 
0.1%
1479.25 8
 
0.1%
1488.25 8
 
0.1%
1400 8
 
0.1%
1533.5 8
 
0.1%
1538.5 8
 
0.1%
1430 8
 
0.1%
1445.5 7
 
0.1%
Other values (4752) 9275
99.1%
ValueCountFrequency (%)
551 1
< 0.1%
559.25 1
< 0.1%
560.5 1
< 0.1%
579 1
< 0.1%
601 1
< 0.1%
601.75 1
< 0.1%
604.75 1
< 0.1%
621.25 1
< 0.1%
637 1
< 0.1%
640.25 1
< 0.1%
ValueCountFrequency (%)
2775 1
< 0.1%
2746 1
< 0.1%
2690.5 1
< 0.1%
2684 1
< 0.1%
2679 1
< 0.1%
2666.5 1
< 0.1%
2665.25 1
< 0.1%
2662 1
< 0.1%
2643 1
< 0.1%
2642.75 1
< 0.1%

PT08.S5(O3)
Real number (ℝ)

High correlation 

Distinct5041
Distinct (%)53.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1032.4225
Minimum221
Maximum2522.75
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size146.2 KiB
2025-04-07T00:08:08.922573image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum221
5-th percentile463.25
Q1733.25
median970
Q31293
95-th percentile1784.25
Maximum2522.75
Range2301.75
Interquartile range (IQR)559.75

Descriptive statistics

Standard deviation404.44261
Coefficient of variation (CV)0.39174139
Kurtosis-0.047560856
Mean1032.4225
Median Absolute Deviation (MAD)269.5
Skewness0.60299368
Sum9660376.9
Variance163573.83
MonotonicityNot monotonic
2025-04-07T00:08:09.055753image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
825.75 10
 
0.1%
904.5 8
 
0.1%
1049.75 8
 
0.1%
779 8
 
0.1%
1023.5 8
 
0.1%
835.5 8
 
0.1%
776.5 7
 
0.1%
922.5 7
 
0.1%
925.75 7
 
0.1%
699.75 7
 
0.1%
Other values (5031) 9279
99.2%
ValueCountFrequency (%)
221 1
< 0.1%
224.75 1
< 0.1%
226.5 1
< 0.1%
232 1
< 0.1%
252 1
< 0.1%
252.5 1
< 0.1%
257 1
< 0.1%
260.5 1
< 0.1%
261 1
< 0.1%
261.5 1
< 0.1%
ValueCountFrequency (%)
2522.75 1
< 0.1%
2522.25 1
< 0.1%
2519.25 1
< 0.1%
2515.25 1
< 0.1%
2493.5 1
< 0.1%
2480.25 1
< 0.1%
2474.75 1
< 0.1%
2465 1
< 0.1%
2452 1
< 0.1%
2433.5 1
< 0.1%

T
Real number (ℝ)

High correlation 

Distinct3733
Distinct (%)39.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean18.231754
Minimum-1.9
Maximum44.6
Zeros0
Zeros (%)0.0%
Negative14
Negative (%)0.1%
Memory size146.2 KiB
2025-04-07T00:08:09.184535image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum-1.9
5-th percentile4.6199999
Q111.725
median17.575
Q324.275001
95-th percentile34.35
Maximum44.6
Range46.5
Interquartile range (IQR)12.550001

Descriptive statistics

Standard deviation8.7823677
Coefficient of variation (CV)0.48170722
Kurtosis-0.44528686
Mean18.231754
Median Absolute Deviation (MAD)6.2499998
Skewness0.32524374
Sum170594.52
Variance77.129983
MonotonicityNot monotonic
2025-04-07T00:08:09.321884image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
15.05000019 15
 
0.2%
23.04999971 15
 
0.2%
20.80000019 13
 
0.1%
24 13
 
0.1%
14.57500005 12
 
0.1%
13.625 11
 
0.1%
21.4749999 11
 
0.1%
15.35000014 11
 
0.1%
21.3499999 11
 
0.1%
13.75 11
 
0.1%
Other values (3723) 9234
98.7%
ValueCountFrequency (%)
-1.899999976 1
< 0.1%
-1.374999989 1
< 0.1%
-1.274999991 2
< 0.1%
-1.199999988 1
< 0.1%
-1.124999985 1
< 0.1%
-0.5500000194 2
< 0.1%
-0.4749999791 1
< 0.1%
-0.2500000056 1
< 0.1%
-0.1500000022 1
< 0.1%
-0.1000000015 1
< 0.1%
ValueCountFrequency (%)
44.60000038 1
< 0.1%
44.34999943 1
< 0.1%
43.42499924 1
< 0.1%
43.12500095 1
< 0.1%
42.82499981 1
< 0.1%
42.79999924 1
< 0.1%
42.77500057 1
< 0.1%
42.67499924 1
< 0.1%
42.625 1
< 0.1%
42.5 1
< 0.1%

RH
Real number (ℝ)

High correlation 

Distinct5265
Distinct (%)56.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean49.189157
Minimum9.1750002
Maximum88.725
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size146.2 KiB
2025-04-07T00:08:09.448672image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum9.1750002
5-th percentile20.45
Q135.8
median49.65
Q362.250002
95-th percentile77.625
Maximum88.725
Range79.55
Interquartile range (IQR)26.450002

Descriptive statistics

Standard deviation17.194081
Coefficient of variation (CV)0.34955022
Kurtosis-0.80681844
Mean49.189157
Median Absolute Deviation (MAD)13.175
Skewness-0.043945335
Sum460262.95
Variance295.63642
MonotonicityNot monotonic
2025-04-07T00:08:09.586097image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
47.75 11
 
0.1%
51.44999981 9
 
0.1%
55.94999981 8
 
0.1%
49.67500019 8
 
0.1%
57.92500019 8
 
0.1%
50.10000038 8
 
0.1%
54.5 8
 
0.1%
50.125 7
 
0.1%
49.05000019 7
 
0.1%
39.40000057 7
 
0.1%
Other values (5255) 9276
99.1%
ValueCountFrequency (%)
9.175000191 1
< 0.1%
9.224999905 1
< 0.1%
9.300000191 1
< 0.1%
9.599999905 1
< 0.1%
9.799999952 1
< 0.1%
9.875000238 1
< 0.1%
9.900000095 1
< 0.1%
9.950000048 1
< 0.1%
9.974999905 1
< 0.1%
10.2249999 1
< 0.1%
ValueCountFrequency (%)
88.72500038 1
< 0.1%
87.17499924 1
< 0.1%
87.07499886 1
< 0.1%
86.95000076 1
< 0.1%
86.62500191 1
< 0.1%
86.55000114 1
< 0.1%
86.52500153 1
< 0.1%
86.47500038 1
< 0.1%
86.00000191 1
< 0.1%
85.69999886 1
< 0.1%

AH
Real number (ℝ)

High correlation 

Distinct9353
Distinct (%)> 99.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.019621
Minimum0.18467902
Maximum2.2310357
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size146.2 KiB
2025-04-07T00:08:09.739581image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum0.18467902
5-th percentile0.39745925
Q10.73227992
median0.98950435
Q31.3066711
95-th percentile1.7204083
Maximum2.2310357
Range2.0463567
Interquartile range (IQR)0.57439114

Descriptive statistics

Standard deviation0.40220309
Coefficient of variation (CV)0.39446334
Kurtosis-0.54660276
Mean1.019621
Median Absolute Deviation (MAD)0.28598896
Skewness0.25939111
Sum9540.5934
Variance0.16176733
MonotonicityNot monotonic
2025-04-07T00:08:09.863804image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1.471325566 2
 
< 0.1%
0.7058010096 2
 
< 0.1%
1.320841244 2
 
< 0.1%
0.7797699428 2
 
< 0.1%
0.7483436266 1
 
< 0.1%
0.7081040235 1
 
< 0.1%
0.7128827373 1
 
< 0.1%
0.6944093366 1
 
< 0.1%
0.7151113922 1
 
< 0.1%
0.7698923251 1
 
< 0.1%
Other values (9343) 9343
99.9%
ValueCountFrequency (%)
0.184679021 1
< 0.1%
0.1861794399 1
< 0.1%
0.1909612085 1
< 0.1%
0.1974686974 1
< 0.1%
0.1987566874 1
< 0.1%
0.2028527693 1
< 0.1%
0.2031033497 1
< 0.1%
0.2061708872 1
< 0.1%
0.2085747799 1
< 0.1%
0.2157357083 1
< 0.1%
ValueCountFrequency (%)
2.231035716 1
< 0.1%
2.180639319 1
< 0.1%
2.176616312 1
< 0.1%
2.171932117 1
< 0.1%
2.139495892 1
< 0.1%
2.136178693 1
< 0.1%
2.124690971 1
< 0.1%
2.119450226 1
< 0.1%
2.117033465 1
< 0.1%
2.116387171 1
< 0.1%

Interactions

2025-04-07T00:08:03.703302image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-07T00:07:47.499686image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-07T00:07:48.951643image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-07T00:07:50.300913image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-07T00:07:52.413736image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-07T00:07:53.961272image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-07T00:07:55.314186image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-07T00:07:56.784373image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-07T00:07:58.133678image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-07T00:07:59.386772image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-07T00:08:00.888866image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-07T00:08:02.100135image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-07T00:08:03.838544image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-07T00:07:47.622193image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
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2025-04-07T00:07:50.447929image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-07T00:07:52.590972image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-07T00:07:54.076242image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
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2025-04-07T00:07:56.691965image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-07T00:07:58.038999image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-07T00:07:59.282348image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-07T00:08:00.795399image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-07T00:08:02.010877image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-07T00:08:03.553389image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Correlations

2025-04-07T00:08:09.965140image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
AHC6H6(GT)CO(GT)NO2(GT)NOx(GT)PT08.S1(CO)PT08.S2(NMHC)PT08.S3(NOx)PT08.S4(NO2)PT08.S5(O3)RHT
AH1.0000.1720.054-0.292-0.1420.1090.173-0.1930.6440.0550.1580.705
C6H6(GT)0.1721.0000.7950.5760.5940.8911.000-0.8480.7370.874-0.1180.259
CO(GT)0.0540.7951.0000.6480.6830.7510.795-0.7000.5290.7420.0110.056
NO2(GT)-0.2920.5760.6481.0000.7960.5850.576-0.6070.1220.623-0.097-0.181
NOx(GT)-0.1420.5940.6830.7961.0000.6100.594-0.6790.1330.6790.184-0.248
PT08.S1(CO)0.1090.8910.7510.5850.6101.0000.891-0.8560.6280.8990.0950.058
PT08.S2(NMHC)0.1731.0000.7950.5760.5940.8911.000-0.8480.7380.873-0.1180.260
PT08.S3(NOx)-0.193-0.848-0.700-0.607-0.679-0.856-0.8481.000-0.522-0.864-0.093-0.093
PT08.S4(NO2)0.6440.7370.5290.1220.1330.6280.738-0.5221.0000.541-0.0610.614
PT08.S5(O3)0.0550.8740.7420.6230.6790.8990.873-0.8640.5411.0000.132-0.025
RH0.158-0.1180.011-0.0970.1840.095-0.118-0.093-0.0610.1321.000-0.536
T0.7050.2590.056-0.181-0.2480.0580.260-0.0930.614-0.025-0.5361.000

Missing values

2025-04-07T00:08:05.522888image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
A simple visualization of nullity by column.
2025-04-07T00:08:05.699587image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

Sample

DateTimeCO(GT)PT08.S1(CO)C6H6(GT)PT08.S2(NMHC)NOx(GT)PT08.S3(NOx)NO2(GT)PT08.S4(NO2)PT08.S5(O3)TRHAH
DateandTime
2004-03-10 18:00:002004-03-1018:00:002.61360.0011.8817231045.50166.0000001056.25113.0000001692.001267.5013.60048.8750010.757754
2004-03-10 19:00:002004-03-1019:00:002.01292.259.397165954.75103.0000001173.7592.0000001558.75972.2513.30047.7000000.725487
2004-03-10 20:00:002004-03-1020:00:002.21402.008.997817939.25131.0000001140.00114.0000001554.501074.0011.90053.9750000.750239
2004-03-10 21:00:002004-03-1021:00:002.21375.509.228796948.25172.0000001092.00122.0000001583.751203.2511.00060.0000000.786713
2004-03-10 22:00:002004-03-1022:00:001.61272.256.518224835.50131.0000001205.00116.0000001490.001110.0011.15059.5750010.788794
2004-03-10 23:00:002004-03-1023:00:001.21197.004.741012750.2589.0000001336.5096.0000001393.00949.2511.17559.1750000.784772
2004-03-11 00:00:002004-03-1100:00:001.21185.003.624399689.5062.0000001461.7577.0000001332.75732.5011.32556.7750000.760312
2004-03-11 01:00:002004-03-1101:00:001.01136.253.326677672.0062.0000001453.2576.0000001332.75729.5010.67560.0000000.770238
2004-03-11 02:00:002004-03-1102:00:000.91094.002.339416608.5045.0000001579.0060.0000001276.00619.5010.65059.6749990.764819
2004-03-11 03:00:002004-03-1103:00:000.61009.751.696658560.75246.8812521705.00113.0755151234.75501.2510.25060.2000010.751657
DateTimeCO(GT)PT08.S1(CO)C6H6(GT)PT08.S2(NMHC)NOx(GT)PT08.S3(NOx)NO2(GT)PT08.S4(NO2)PT08.S5(O3)TRHAH
DateandTime
2005-04-04 05:00:002005-04-0405:00:000.5888.251.307608528.0076.51076.5053.1987.00577.5010.40000059.8750000.754964
2005-04-04 06:00:002005-04-0406:00:001.11030.504.359341730.25182.2760.0093.01129.00905.009.55000063.1500000.753129
2005-04-04 07:00:002005-04-0407:00:004.01383.5017.3642401220.75593.7470.25154.61600.001457.259.67500061.9249990.744608
2005-04-04 08:00:002005-04-0408:00:005.01446.0022.3932331361.50586.2414.75173.61776.501704.5013.55000048.8750000.755337
2005-04-04 09:00:002005-04-0409:00:003.91296.5013.5523931102.00522.7506.75186.51375.251582.5018.15000136.2750010.748652
2005-04-04 10:00:002005-04-0410:00:003.11314.2513.5296051101.25471.7538.50189.81374.251728.5021.85000029.2500000.756824
2005-04-04 11:00:002005-04-0411:00:002.41162.5011.3551571027.00353.3603.75179.21263.501269.0024.32500023.7250000.711864
2005-04-04 12:00:002005-04-0412:00:002.41142.0012.3745381062.50293.0603.25174.71240.751092.0026.90000018.3500000.640649
2005-04-04 13:00:002005-04-0413:00:002.11002.509.547187960.50234.5701.50155.71041.00769.7528.32500013.5500000.513866
2005-04-04 14:00:002005-04-0414:00:002.21070.7511.9320601047.25265.2654.00167.71128.50816.0028.50000013.1250000.502804